Classical radiation absorbed dosimetry operates to determine the average energy deposited per unit mass,
J/kg, but cannot predict the radiobiological effects in biological tissue for all types of radiation.
Early attempts at understanding cellular radiation effects recognized that knowledge of the energy distribution at a scale comparable to the structures affected by irradiation (“ending point”) was essential, and hence on a cellular level or DNA level. Consequently, the study of radiation effects on living cells is termed microdosimetry.
One of the factors affecting local energy deposition is Linear Energy Transfer (LET), that is, the loss of energy per unit distance along the path of a charged particle. With smaller targets, deterministic energy deposition becomes stochastic and depends on the target size and spatial pattern of energy deposited by radiation (by charged particles). It limits the correlation of the LET approach with radiobiological effects.
There are several reasons for the limitations in the LET concept. Firstly, delta ray energy distribution and its relationship to spatial dose distribution are not adequately considered. Particles with different velocities and charges can have the same LET but it is the particle velocity that largely determines the energy distribution of delta rays. In microscopic volumes, the delta ray distribution may be a significant factor in the spatial distribution of energy, particularly at higher ion energies and small site sizes.
Finally, LET, being a non-stochastic average quantity, does not account for the random fluctuations in energy deposition which manifest as clustering of energy deposition and range straggling. The variance due to straggling may exceed the path length variations at high ion energies and small site sizes.
These limitations in LET lead to the formulation of a set of measurable stochastic quantities that provide the fundamental basis for the field of microdosimetry. The two principal quantities are specific energy z=ε/m (where ε is energy deposited in a volume by a single energy deposition event and m is a mass of the sensitive volume-target SV) and lineal energy y, which is defined as the ratio of ε to l, the mean chord length in that volume. Hence:
                    y        =                  ɛ                      l            _                                              (        1        )            
Lineal energy is commonly presented in units of key μm−1. The mean chord length in a volume is the mean length of randomly orientated chords in that volume, that is
                              l          _                =                              4            ⁢            V                    S                                    (        2        )            
where V is the volume of the microscopic sensitive volume-target (SV) and S is the surface area of the SV. The SV must clearly be well defined.
It is the goal of experimental microdosimetry to measure these quantities in well-defined microscopic volumes, and is hence referred to as regional microdosimetry. Regional microdosimetry is concerned with the measurement of energy deposition in sites and it is the principal objective of experimental microdosimetry. There is a link between microdosimetric experimental quantities and the observed effects of radiation on biological cells.
The probability distribution of lineal energy f(y) or as a dose distribution d(y) (fraction of energy versus event size) are fundamental functions in regional microdosimetry. The relationship between f(y) and d(y) is:
                              d          ⁡                      (            y            )                          =                              yf            ⁡                          (              y              )                                                          y              _                        F                                              (        3        )            
where yF is the average lineal energy for a particular radiation field and secondary charged particle in a medium of interest, and:
                                          y            _                    F                =                              ∫            0            ∞                    ⁢                                    yf              ⁡                              (                y                )                                      ⁢                          ⅆ              y                                                          (        4        )            
The dose distribution relationship reflects the fact that higher lineal energies deposit a higher dose.
From the single event lineal energy distribution and the site geometry one may calculate all microdosimetric distributions of interest using the formulae presented above. The representation of these fundamental microdosimetric spectra is traditionally displayed as a log-linear plot with the ordinate multiplied by y, such that the area under the curve delimited by two values of y is proportional to the fraction of events (for f(y)) or the fraction of dose(for d(y)) delivered by events in this range of lineal energy values. This representation accommodates the wide lineal energy range often observed in microdosimetric spectra (from 0.01 keV/μm to several hundred keV/μm) but requires further scaling to preserve the dose to area correspondence.
Microdosimetry requires instrumentation for measurements of energy δ deposited in a cellular (or sub cellular) SV of interest (whether tissue or water), event-by-event from secondary particles generated in the medium of interest by the radiation field. Of use in such measurements was the development in the early 1950s of the low-pressure gas proportional counter, also referred to as the Rossi counter. Adjustment of sensitive volume up to 1 micron is possible by changing of the gas pressure in a counter. Tissue-Equivalent Proportional Counters (TEPCs) of this type (which are tissue equivalent owing to the tissue equivalence of the gas and surrounding walls) have several shortcomings:    1. TEPCs require a gas supply system that are inconvenient in many applications;    2. TEPCs are large, up to 1 to 2 cm in diameter, which limits their use where spatial resolution is required;    3. TEPCs require high voltage biases; up to 2 kV; and    4. TEPCs suffer from the “wall effect” and other physical size related effects, being much larger than the cell structures, leading to artefacts in microdosimetric spectra.
Microdosimetric spectra can be converted to radiobiological characteristics of the radiation field by convolution with a quality coefficient Q over the range of lineal energies, which reflects increasing probability of cell inactivation with increasing lineal event energy. The coefficient Q is determined by the ICRU (the International Commission on Radiation Units and Measurements) and based on experimental in vitro cell survival measurements; its analytical values are tabulated in Table 1 as a function of L, the unrestricted linear energy transfer in water.
TABLE 1Quality coefficient Q (L)L (keV μm−1)Q (L) <10110-1000.32L-2.2>100300/L0.5Q is thus a measure of the main difference between absorbed dosimetry and equivalent (radiobiological) dosimetry of radiation fields.
Solid state detectors are very good owing to their small SV size; this is why in some situations minidosimetry is used instead of microdosimetry. In minidosimetry the small SV of the detector is used to measure absorbed dose or dose rate but with high spatial resolution. For example, MOSFET detectors (which have a very small SV of micron or submicron size) are able to measure absorbed doses with 1 micron spatial resolution, but cannot distinguish the energy deposited in the SV due to a particular event. The output signal instead represents the integral of many events depositing energy in the SV. This occurs with many solid state detectors, such as dosimetric diodes working in current mode, TLDs (thermoluminescent dosimeters) and film.
However, passive solid state detectors can be used to some extend in microdosimetry. For example, glow peaks in some TLDs are sensitive to LET of particles that are associated with energy deposition on the micron and submicron level. These detectors are not a suitable substitution for TEPCs, as do not have proper LET resolution and cannot be used in real time dosimetry.
Another passive microdosimetry detector device—disclosed in U.S. Pat. No. 5,596,199—records the energy deposition of incident radiation using an array of microstructure non-volatile memory devices. The charge from incident charge particles is stored in an electrically insulated (floating) gate, micron or submicron scale SV, of a FAMOS transistor. When this charge exceeds the threshold level the state of the memory cell changes, so the number of cells that have changed state is equal to the number of events that have deposited energy above the threshold. A predetermined initial charge is stored in each cell, which makes the charge increment required to change the state of the cells variable. This is claimed to provide a spectroscopy of the deposited energies, but it is a discreet spectroscopy rather than analogue or real spectroscopy. There can be uncertainty in the change of state of a memory cell, as—rather than resulting from a single event in the SV—a change of state can be due to several consecutive events, thereby giving an incorrect indication of the radiation field. Owing to the passive mode of operation, the charge deposited in the SV is therefore less than on a floating gate. The charge deficit due to recombination depends on the LET of the particle.
Recombination of charge in the gate oxide is well known in MOSFET detectors, and reduces the utility of MOSFET detectors for dosimetry in proton and heavy ions fields (even in an active mode). This microdosimeter is designed principally to distinguish the gamma and neutron components of a radiation field, but it can only with difficultly obtain dose equivalent using the weighting coefficient Q in arbitrary radiation fields as recommended by the ICRU.
Another approach, based on the parallel connection of micron scale Si detectors (p-n junctions), provides an active array of micron scale SVs. In this approach reverse biased Si detectors with micron scale silicon SVs—comparable in size to biological cells—are connected to a nuclear spectroscopy setup. The small area of the array of p-n junctions allows pile up to be avoided, provided that charge is generated in a single SV only (which is true in most situations). This condition does not hold, however, if the charged particle traverses an SV in a direction substantially parallel to the surface of the chip. In such cases energy can be deposited in two cells simultaneously, providing a greater charge than if it were deposited in a single SV. Spectroscopy information can be converted to dose equivalent using a weighting factor recommended by the ICRU. This technique has been demonstrated using planar arrays of p-n junctions of NMOS and CMOS SRAM with an SV size of 44×44×3 microns. Applications of such planar arrays of p-n junctions for regional microdosimetry are limited owing to uncertainty in the average chord, charge collection efficiency within the SV, overlayers and shape of the SV. Increasing the total area of the p-n junction array leads to increases in the noise owing to an increase in capacitance that reduces the minimal LET detected by the microdosimeter. A segmentation approach with several parallel readout spectroscopy channels has been suggested to reduce the noise of the microdosimeter; this method has been demonstrated in the separation of gamma-neutron field without any qualitative or quantitative (dose equivalent) characterization of the radiation field.
Charge collection spectroscopy in a micron size array of planar P-N junctions (SVs) of a memory chip (SRAM) strongly depends on the fabrication technology, the angle of incidence and SV shape. Hence, interpretation of MCA spectra for conversion to dose equivalent is complex.
A solid state silicon microdosimeter based on a parallel array of p-n junctions for measurements of tissue equivalent microdosimetric spectra has also been investigated. The viability of measuring integral dose and microdosimetric spectra simultaneously at the same point in a water phantom in fast neutron therapy beam has been demonstrated. A new generation solid state microdosimeter with an array of parallel p-n junctions manufactured on SOI (Silicon-on-Insulator) with SV thicknesses of 2, 5 and 10 μm have been produced and investigated. RPP (right angle parallelepiped) shaped 30×30 μm planar SVs (outer P+ contact) and 10×10 μm care (N+P p-n junction) regions were connected in parallel producing arrays of 4800 and 10000 cells. FIG. 1 is a schematic view of such an SV at 100, comprising a 3D-fragment of an SOI p-n junction array. The SOT p-n junction array has a better defined SV than have arrays of p-n junctions on a bulk material or commercial SRAM.
It has been demonstrated by Monte Carlo simulations that, for most charged particle of interest (α-particles, protons, electrons and some heavy ions typical for radiation therapy), a 3×3×3 μm silicon SV is equivalent to 5×5×5 μm of soft tissue. This amounts to a conversion linear scaling coefficient ζ=0.63. It has also been demonstrated that solid sate microdosimetry spectra can be converted to tissue equivalent (TE) microdosimetry spectra, that is, to dose equivalent. FIG. 2 is a plot 200 of microdosimetric spectra obtained with gas TEPC and 10 μm SOI 4800 parallel cell microdosimeter using developed conversion, at depths of 2.5 and 10 cm in a water phantom on an FNT (Fast Neutron Therapy) beam after TE conversion. These spectra were obtained in a water phantom at the FNT facility, Harper Hospital, Detroit, USA. (The tissue equivalent microdosimetric spectrum obtained with an SOT microdosimeter at depth 2.5 cm in water is shown at 202 and at depth 10 cm in water at 204; the tissue equivalent microdosimetric spectrum obtained by TEPC at depth 2.5 cm in water is shown at 206 and at depth 10 am in water at 208.)
It is apparent from FIG. 2 that an SOI microdosimeter with an array of planar p-n junctions is essentially unable to measure events with LET (Lineal Energy Transfer) less than 1-2 keV/μm; this is due to detector noise. This low LET part of the spectra is related to high energy gamma radiation, but it can dominate in certain radiation fields and is important to measure.
Detailed investigations of charge collection in a single SV of an SOI planar RPP SVs using IBIC ion microbeam has shown non-uniformity of charge collection, with increasing charge deficit laterally away from the centre of SV. FIGS. 3A, 3B and 3C are charge collection images, obtained with 3 MeV α-particle scanning microbeam in 30×30 μm planar RPP SVs in a 10 μm SOI microdosimeter. FIG. 3A corresponds to a p-n junction bias of 0 V, FIG. 3B to a p-n junction bias of 5 V and FIG. 3C to a p-n junction bias of 10 V. Charge collection is almost 100% in the central part of the SV under the N+P p-n junction and diminishes laterally from the central axis of the SV owing to the lessening electrical field.
Losses of charge in a planar P-N junction cell due to recombination prevents the accurate measurement of energy deposited in a cell from a single event, thus reducing the accuracy of equivalent dosimetry. This is a disadvantage of the current design of solid state microdosimeters with planar p-n junction. Also, reducing the size of the SV to reduce the charge deficit reduces the energy deposited in the SV, and this technique is also limited by the noise of the detector.
Two charged particles with the same LET can have different delta electron track structures, which are dependent on the speed of the charged particle. As the size of the SV is reduced, high energy delta electrons can be deposited in neighbouring cells (viz. SVs) and will be accepted as single events in an SV owing to the parallel connection of the p-n junctions. This produces an error in the determination of the cluster of deposited energy in a single SV. This effect is typical for high energy heavy ions in deep space radiation with delta electron energies up to 1 MeV.